American express job opportunities 2024
An Analyst in Data Science is responsible for extracting meaningful insights from complex data sets to drive strategic decision-making. This role involves analyzing large volumes of data using statistical and machine learning techniques to identify trends, patterns, and anomalies. The analyst collaborates with cross-functional teams to translate data findings into actionable business strategies. They are proficient in programming languages such as Python or R, and skilled in data visualization tools like Tableau or Power BI. Strong analytical thinking, problem-solving abilities, and effective communication skills are essential to articulate insights and recommendations to stakeholders.
About company :
American Express, often abbreviated as Amex, is a globally renowned financial services corporation known for its credit card, charge card, and travel-related services. Founded in 1850 and headquartered in New York City, American Express has built a reputation for exceptional customer service and innovative financial solutions. The company offers a range of products and services including personal and corporate credit cards, travel services, and financial planning.
American Express is distinguished by its strong brand and loyalty programs, such as the Membership Rewards program, which provides cardholders with extensive rewards and benefits. The company also emphasizes security and fraud prevention, ensuring that its customers’ financial transactions are safe and reliable.
Career development at AWS includes numerous opportunities for advancement across the organization to support your career aspirations. We offer comprehensive training programs to help you develop the skills needed for success in your role. For those interested in travel, support engineers have had the opportunity to present training sessions or participate in focused summits at various sites or AWS events.
Job role :
The successful candidate will be responsible for managing and controlling model risk, specifically related to next-generation Artificial Intelligence (AI) and Machine Learning (ML) models. This role aims to enhance model excellence, bolster long-term shareholder value, and adapt to the evolving landscape of model development, external environment changes, and increased regulatory expectations.
- Conducting independent oversight of enterprise-wide models, focusing on AI and ML models used for marketing, credit, fraud, and other business or risk types.
- Performing gap assessments and establishing a robust framework to strengthen model risk controls and meet elevated regulatory standards.
- Conducting research to identify opportunities for enhancing model excellence and driving business impact.
Communicating results to partners, senior leadership, and various model committees.
Job details :
| Company Name | American Express |
| Role | Data Analyst |
| Qualification | Master degree |
| Location | Haryana |
| Experience | 0-4 years |
Technical Expertise :
Proficiency in at least one data manipulation tool (e.g., R, Java, SQL, SAS) is essential. Strong expertise in Data Science, Machine Learning, and Artificial Intelligence, encompassing coding proficiency and mastery of supervised and unsupervised techniques. Skills include active learning, transfer learning, neural networks, decision trees, reinforcement learning, graphical models, Gaussian processes, Bayesian models, and map reduce techniques. Familiarity with advanced algorithms such as Random Forest, Gradient Boosting, Deep Learning, and Text Mining Algorithms is required. These competencies are pivotal for leveraging complex data sets and driving innovative solutions in the realm of AI and ML.
In addition to technical prowess, hands-on experience in applying these methodologies to real-world problems is crucial. Proficiency in implementing scalable solutions and optimizing algorithms for performance is expected. The ability to interpret and communicate findings to stakeholders from diverse backgrounds is also essential. A strong foundation in statistical analysis and hypothesis testing further enhances the capability to derive actionable insights from data. Continual learning and adaptation to new techniques and technologies in the rapidly evolving field of AI and ML are emphasized, ensuring the ability to stay ahead in leveraging cutting-edge approaches for business impact.
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